Circuit Approximation Using Single and Multi-Objective Cartesian GP

@InProceedings{Vasicek:2015:EuroGP,
author = "Zdenek Vasicek and Lukas Sekanina",
title = "Circuit Approximation Using Single and Multi-Objective
{Cartesian GP}",
booktitle = "18th European Conference on Genetic Programming",
year = "2015",
editor = "Penousal Machado and Malcolm I. Heywood and
James McDermott and Mauro Castelli and
Pablo Garcia-Sanchez and Paolo Burelli and Sebastian Risi and Kevin Sim",
series = "LNCS",
volume = "9025",
publisher = "Springer",
pages = "217--229",
address = "Copenhagen",
month = "8-10 " # apr,
organisation = "EvoStar",
note = "Best Paper",
keywords = "genetic algorithms, genetic programming, Cartesian
genetic programming, Evolutionary design, Approximate
computing, Approximate circuits, Multi-objective
approach: Poster",
isbn13 = "978-3-319-16500-4",
DOI = "doi:10.1007/978-3-319-16501-1_18",
abstract = "In this paper, the approximate circuit design problem
is formulated as a multi-objective optimisation problem
in which the circuit error and power consumption are
conflicting design objectives. We compare
multi-objective and single-objective Cartesian genetic
programming in the task of parallel adder and
multiplier approximation. It is analysed how the
setting of the methods, formulating the problem as
multi-objective or single-objective, and constraining
the execution time can influence the quality of
results. One of the conclusions is that the
multi-objective approach is useful if the number of
allowed evaluations is low. When more time is
available, the single-objective approach becomes more
efficient.",
notes = "Part of \cite{Machado:2015:GP}EuroGP'2015 held in
conjunction with EvoCOP2015, EvoMusArt2015 and
EvoApplications2015",
}